Video compression standards, such as MPGE-2, MPEG-4, H.263 and H.264/AVC, have been extensively used in video related applications. The performance of a video processor with the compression standards is often limited by frame memory size and system bandwidth. To speedup a video processor, frame memory compression is applied, which could be used to reduce frame memory size by compressing the data to be stored in frame memory. Additionally, since data stored in frame memory is reduced by FMC, the amount of data transferred on the bus could be thus greatly lessened to meet the bandwidth constraint. Existing techniques on the frame memory compression may be categorized into two types. One type of FMC is based on spatial domain. The other type of FMC is based on frequency domain.
The FMC based on spatial domain utilizes the correlation of pixels in spatial domain to predict pixel values. For example, some techniques for reducing buffered-frame memory sizes and accesses in a video Codec, such as H.264/AVC, decide an associated storage type for each micro block (MB) through a new added decision unit, and perform a simple compression according to the associated storage type of the MB. Some FMC algorithms embed a compression unit between a processing core and an external memory, compute results for a plurality of prediction modes by taking a 4×4 block as a compression unit, and select a best computed compression result. One frame memory recompression technique for video codec uses a pixel-based lossless compression method, and utilizes an address table to preserve random accessibility of coding unit. One technique designs a coding scheme with law latency and variable length by taking latency into consideration.
FIG. 1 shows an exemplary schematic view illustrating a FMC technique based on spatial domain. The technique uses a fixed compression ratio and near-lossless FMC to reduce the bandwidth of hardware components and decrease the usage of frame memory. As shown in FIG. 1, a 4×4 block is taken as a compression unit, The FMC technique utilizes 8 prediction modes (Mode 1˜Mode 8) and associates simple quantization, differential pulse code modulation (DPCM), and variable length coding (VLC) such as Golomb-Rice coding, to perform frame memory compression. Using intra prediction modes for performing FMC may require high complexity, and do not show much significance on the compression results for small compressed blocks.
The FMC based on frequency domain converts the pixels from spatial domain into frequency domain, and utilizes clustering effect of power energy in frequency domain for compressing data. For example, one video memory reduction technique uses hierarchical transform such as Harr transform, to convert the pixels from spatial domain into frequency domain, and performs quantization and run length coding on the obtained transformation coefficients. One lossy FMC technique considers gray-level pixel data, and uses fixed or variable quantization to perform frame memory compression. Some techniques use modified Hadamard transform and adaptive Golomb-Rice coding to perform frame memory compression for display devices. Some techniques use modified Hadamard transform and adaptive Golomb-Rice coding to perform frame memory compression, by considering a fixed compression efficiency of 50%. Some technique uses discrete Cosine transform and modified bit plane zonal coding to implement a frame compressor for mobile video applications. The FMC based on frequency domain may require high computation or hardware complexity and may not be proper for the applications with low-latency requirements.